继续跟中华石杉老师学习ES,第十四篇
课程地址: https://www.roncoo.com/view/55
https://www.elastic.co/guide/en/elasticsearch/reference/7.2/query-dsl-multi-match-query.html
cross-fields搜索,一个唯一标识,跨了多个field。
比如一个人,标识,是姓名;一个建筑,它的标识是地址。
姓名可以散落在多个field中,比如first_name和last_name中,地址可以散落在country,province,city中。
跨多个field搜索一个标识,比如搜索一个人名,或者一个地址,就是cross-fields搜索
初步来说,如果要实现,可能用most_fields比较合适。因为best_fields是优先搜索单个field最匹配的结果,cross-fields本身就不是一个field的问题了。
构造数据
POST /forum/article/_bulk
{ "update": { "_id": "1"} }
{ "doc" : {"author_first_name" : "Peter", "author_last_name" : "Smith"} }
{ "update": { "_id": "2"} }
{ "doc" : {"author_first_name" : "Smith", "author_last_name" : "Williams"} }
{ "update": { "_id": "3"} }
{ "doc" : {"author_first_name" : "Jack", "author_last_name" : "Ma"} }
{ "update": { "_id": "4"} }
{ "doc" : {"author_first_name" : "Robbin", "author_last_name" : "Li"} }
{ "update": { "_id": "5"} }
{ "doc" : {"author_first_name" : "Tonny", "author_last_name" : "Peter Smith"} }
执行查询
GET /forum/article/_search
{
"query": {
"multi_match": {
"query": "Peter Smith",
"type": "cross_fields",
"fields": [
"author_first_name",
"author_last_name"
]
}
}
}
等同于 most_fileds
GET /forum/article/_search
{
"query": {
"multi_match": {
"query": "Peter Smith",
"type": "most_fields",
"fields": [
"author_first_name",
"author_last_name"
]
}
}
}
返回结果
{
"took": 2,
"timed_out": false,
"_shards": {
"total": 1,
"successful": 1,
"skipped": 0,
"failed": 0
},
"hits": {
"total": 3,
"max_score": 2.3258216,
"hits": [
{
"_index": "forum",
"_type": "article",
"_id": "1",
"_score": 2.3258216,
"_source": {
"articleID": "XHDK-A-1293-#fJ3",
"userID": 1,
"hidden": false,
"postDate": "2017-01-01",
"tag": [
"java",
"hadoop"
],
"tag_cnt": 2,
"view_cnt": 30,
"title": "this is java and elasticsearch blog",
"content": "i like to write best elasticsearch article",
"sub_title": "learning more courses",
"author_first_name": "Peter",
"author_last_name": "Smith"
}
},
{
"_index": "forum",
"_type": "article",
"_id": "5",
"_score": 1.7770995,
"_source": {
"articleID": "DHJK-B-1395-#Ky5",
"userID": 3,
"hidden": false,
"postDate": "2019-05-01",
"tag": [
"elasticsearch"
],
"tag_cnt": 1,
"view_cnt": 10,
"title": "this is spark blog",
"content": "spark is best big data solution based on scala ,an programming language similar to java",
"sub_title": "haha, hello world",
"author_first_name": "Tonny",
"author_last_name": "Peter Smith"
}
},
{
"_index": "forum",
"_type": "article",
"_id": "2",
"_score": 0.5389965,
"_source": {
"articleID": "KDKE-B-9947-#kL5",
"userID": 1,
"hidden": false,
"postDate": "2017-01-02",
"tag": [
"java"
],
"tag_cnt": 1,
"view_cnt": 50,
"title": "this is java blog",
"content": "i think java is the best programming language",
"sub_title": "learned a lot of course",
"author_first_name": "Smith",
"author_last_name": "Williams"
}
}
]
}
}
5.x版本中可能会出现: Peter Smith,匹配author_first_name,匹配到了Smith,这时候它的分数很高,为什么???
因为IDF分数高,IDF分数要高,那么这个匹配到的term(Smith),在所有doc中的出现频率要低,author_first_name field中,Smith就出现过1次
Peter Smith这个人,doc 1,Smith在author_last_name中,但是author_last_name出现了两次Smith,所以导致doc 1的IDF分数较低
cross-fields弊端